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Reversal of muscle fatigue during 16 h of heavy intermittent cycle exercise

2004· article· en· W1973993458 on OpenAlexaff
H. J. Green, Todd A. Duhamel, Shane Ferth, Graham P. Holloway, Melissa M. Thomas, A. Russell Tupling, S. M. Rich, Justine E. Yau

Bibliographic record

VenueJournal of Applied Physiology · 2004
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMuscle fatigueMedicineCardiologyPhysical exercisePhysical medicine and rehabilitationExercise physiologyPhysical therapyInternal medicineElectromyography

Abstract

fetched live from OpenAlex

This study examined the effects of extended sessions of heavy intermittent exercise on quadriceps muscle fatigue and weakness. Twelve untrained volunteers (10 men and 2 women), with a peak oxygen consumption of 44.3 +/- 2.3 ml.kg(-1).min(-1), exercised at approximately 91% peak oxygen consumption for 6 min once per hour for 16 h. Muscle isometric properties assessed before and after selected repetitions (R1, R2, R4, R7, R12, and R15) were used to quantitate fatigue (before vs. after repetitions) and weakness (before vs. before repetitions). Muscle fatigue at R1 was indicated by reductions (P < 0.05) in peak twitch force (135 +/- 13 vs. 106 +/- 11 N) and by a reduction (P < 0.05) in the force-frequency response, which ranged between approximately 53% at 10 Hz (113 +/- 12 vs. 52.6 +/- 7.4 N) and approximately 17% at 50 Hz (324 +/- 27 vs. 270 +/- 30 N). No recovery of force, regardless of stimulation frequency, was observed during the 54 min between R1 and R2. At R2 and for all subsequent repetitions, no reduction in force, regardless of stimulation frequency, was generally found after the exercise. The only exception was for R2, where, at 20 Hz, force was reduced (P < 0.05) by 18%. At R15, force before repetitions for high frequencies (i.e., 100 Hz) returned to R1 (333 +/- 29 vs. 324 +/- 27 N), whereas force at low frequency (i.e., 10 Hz) was only partially (P < 0.05) recovered (113 +/- 12 vs. 70 +/- 6.6 N). It is concluded that multiple sessions of heavy exercise can reverse the fatigue noted early and reduce or eliminate weakness depending on the frequency of stimulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.281
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2004
Admission routes1
Has abstractyes

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